In generating a three-dimensional model by using an image which is obtained by imaging a three-dimensional object, a great number of images captured from various view points are necessary. Further, with respect to recognition of a three-dimensional object by using an image which is obtained by imaging the three-dimensional object from an arbitrary view point or with respect to learning of a classifier that recognizes the three-dimensional object, it is useful to use a great number of images captured from various view points. The learning of the classifier is to set or adjust a parameter of the classifier by using a great amount of data that continually increases according to learning. According to learning, optimum control is realized while adjustment is being made. Various methods have been proposed so far as a method for acquiring a great number of images obtained by imaging an object from various view points.
Japanese Patent Laid-Open No. 2007-72537 discusses an imaging apparatus including a plurality of imaging apparatuses and a rotation base where an object is mounted. The imaging apparatus references a feature point of the object. According to such an apparatus, the orientation of the object can be changed and a complete periphery image of the object can be captured.
Japanese Patent Laid-Open No. 2004-139294 discusses a multi view-point image processing program using a plurality of markers each of which serves as a reference of a view point position. According to such a method, as is with patent literature 1, without using a large-scale imaging apparatus, images of an object captured according to imaging from various view points can be acquired.
Regarding generation of a highly-accurate three-dimensional model or learning of a classifier that performs arbitrary view-point object recognition, it is desirable if a great number of images can be acquired which is performed by imaging the object evenly from various view points. However, with respect to the above-described method, an optimum method for evenly imaging the object from various view points is not provided or a simple method for realizing such imaging is not provided.
Further, with respect to generation of an improved three-dimensional model or improved learning of a classifier that performs arbitrary view-point object recognition, it is useful if the image is acquired according to a shape of the object. For example, it is useful if an image of a portion whose structure is complex is acquired in detail from a number of view points. However, the portion of the view points which should be densely arranged in capturing a portion of the object is not clear. Further, even if a portion where view points should be densely arranged is given, a method for simply acquiring such an image is not provided.